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Auflistung nach Autor:in "Tessone, Claudio Juan"

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  • Konferenzbeitrag
    Automated software remodularization based on move refactoring - A complex systems approach
    (Software-engineering and management 2015, 2015) Scholtes, Ingo; Zanetti, Marcelo Serrano; Tessone, Claudio Juan; Schweitzer, Frank
    Modular design is a desirable characteristic that fosters the comprehensibility and thus maintainability of software systems. While many software systems are initially created in a modular way, over time modularity typically degrades. In our work, we propose an automated strategy to remodularize software based on move refactorings, i.e. moving classes between packages without changing other aspects of the source code. Taking a complex systems perspective, our approach applies network theory to the dynamics of software dependency structures. Drawing inspiration from statistical physics, we use the Potts Spin Model and turn it into a stochastic remodularization algorithm which is based on probabilistically moving classes between modules. We test our method on 39 open source JAVA software projects. Comparing the modular structure produced by developers with that optimized by our algorithm, we find that our method is able to improve modularity by an average of $166 \pm 77$ percent. Our work highlights the potential of interdisciplinary applications of methods from the statistical physics perspective on complex systems to software engineering.
  • Konferenzbeitrag
    Categorizing bugs with social networks: A case study on four Open Source software communities
    (Software Engineering 2014, 2014) Scholtes, Ingo; Serrano Zanetti, Marcelo; Tessone, Claudio Juan
  • Zeitschriftenartikel
    Organic Design of Massively Distributed Systems: A Complex Networks Perspective
    (Informatik-Spektrum: Vol. 35, No. 2, 2012) Scholtes, Ingo; Tessone, Claudio Juan
    The vision of Organic Computing addresses challenges that arise in the design of future information systems that are comprised of numerous, heterogeneous, resource-constrained and error-prone components. The notion organic highlights the idea that, in order to be manageable, such systems should exhibit self-organization, self-adaptation and self-healing characteristics similar to those of biological systems. In recent years, the principles underlying these characteristics are increasingly being investigated from the perspective of complex systems science, particularly using the conceptual framework of statistical physics and statistical mechanics. In this article, we review some of the interesting relations between statistical physics and networked systems and discuss applications in the engineering of organic overlay networks with predictable macroscopic properties.